class_docstr: This `Field` represents a list of string tokens.  Before constructing this object, you need
  to tokenize raw strings using a :class:`~allennlp.data.tokenizers.tokenizer.Tokenizer`.
  
  Because string tokens can be represented as indexed arrays in a number of ways, we also take a
  dictionary of :class:`~allennlp.data.token_indexers.token_indexer.TokenIndexer`
  objects that will be used to convert the tokens into indices.
  Each `TokenIndexer` could represent each token as a single ID, or a list of character IDs, or
  something else.
  
  This field will get converted into a dictionary of arrays, one for each `TokenIndexer`.  A
  `SingleIdTokenIndexer` produces an array of shape (num_tokens,), while a
  `TokenCharactersIndexer` produces an array of shape (num_tokens, num_characters).
code: def batch_tensors(
      self, tensor_list: List[TextFieldTensors]
  ) -> TextFieldTensors:
      # This is creating a dict of {token_indexer_name: {token_indexer_outputs: batched_tensor}}
      # for each token indexer used to index this field.
      indexer_lists: Dict[
          str, List[Dict[str, torch.Tensor]]
      ] = defaultdict(list)
      for tensor_dict in tensor_list:
          for indexer_name, indexer_output in tensor_dict.items():
              indexer_lists[indexer_name].append(indexer_output)
      batched_tensors = {
          # NOTE(mattg): if an indexer has its own nested structure, rather than one tensor per
          # argument, then this will break.  If that ever happens, we should move this to an
          # `indexer.batch_tensors` method, with this logic as the default implementation in the
          # base class.
          indexer_name: util.batch_tensor_dicts(indexer_outputs)
          for indexer_name, indexer_outputs in indexer_lists.items()
      }
      return batched_tensors
  
imports: from collections import defaultdict
  from copy import deepcopy
  from typing import Dict, List, Optional, Iterator
  import textwrap
  from spacy.tokens import Token
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.data.fields.sequence_field import SequenceField
  from allennlp.data.tokenizers import Token
  from allennlp.data.token_indexers.token_indexer import TokenIndexer, IndexedTokenList
  from allennlp.data.vocabulary import Vocabulary
  from allennlp.nn import util
label_desc: Use image node_id 10 for calling the TextField obj's underlying member method code with example usage: obj.batch_tensors(tensor_list) and returns: batched_tensors